10967/257 - QDB Compounds

QsarDB Repository

Oja, M.; Sild, S.; Piir, G.; Maran, U. Intrinsic aqueous solubility: mechanistically transparent data-driven modeling of drug substances. Pharmaceutics 2022, 14, 2248.

Compound

ID:sc111
Name:Didanosine
Description:
Labels:
CAS:
InChi Code:InChI=1S/C10H12N4O3/c15-3-6-1-2-7(17-6)14-5-13-8-9(14)11-4-12-10(8)16/h4-7,15H,1-3H2,(H,11,12,16)/t6-,7+/m0/s1

Properties

logS0: Intrinsic aqueous solubility from single source [log(mol/L)]

ValueSource or prediction
-1.24

Avdeef, A. Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database. ADMET DMPK 2020, 8, 29–77. http://dx.doi.org/http://doi.org/10.5599/admet.766

-2.422

M1: Model with Dragon descriptors from training set 1 (Loose test set)

-2.422

M1: Model with Dragon descriptors from training set 1 (Test sets together)

logS0a: Intrinsic aqueous solubility from multiple sources [log(mol/L)]

ValueSource or prediction
-1.24

Avdeef, A. Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database. ADMET DMPK 2020, 8, 29–77. http://dx.doi.org/http://doi.org/10.5599/admet.766

-1.726

M2: Model with RDKit descriptors from training set 2 (Loose test set)

-1.726

M2: Model with RDKit descriptors from training set 2 (Test sets together)

-1.242

M3: Model with PaDEL and XLOGS descriptors from training set 2 (Loose test set)

-1.242

M3: Model with PaDEL and XLOGS descriptors from training set 2 (Test sets together)

-1.796

M_cons: Consensus model (average of predictions from M1, M2 and M3) (Loose test set)

-1.796

M_cons: Consensus model (average of predictions from M1, M2 and M3) (Test sets together)